MULTIFRACTAL DISCRIMINATION MODEL (MDM) OF HIGH-FREQUENCY PUPIL DIAMETER MEASUREMENTS FOR HUMAN-COMPUTER INTERACTION - Quantitative Medical Data Analysis Using Mathematical Tools and Statistical Techniques - page 334

1. Introduction
The discipline of human-computer interaction (HCI) strives to evaluate and
improve user performance and interaction with information technologies for
users with varying abilities and needs across many dierent contexts. Men-
tal workload has long been recognized as an important component of human
performance during interaction with complex systems 1 , such as comput-
ers. Notably, extreme levels of workload (high and low) have been shown to
be predictive of performance decrements for dierent users under dierent
conditions. To this end, this study examines the workload experienced by
users with visual impairments during the performance of a computer-based
task.
Previous investigations have examined the interactions of users with vi-
sual impairment related to Age-related Macular Degeneration (AMD) 2;3;4 .
AMD is one of the leading causes of visual impairment and blindness for
individuals 55 years of age and older 5 . Since the majority of information
oered by computers is presented visually on a screen, these users are at a
clear disadvantage. Research eorts directed towards the characterization of
computer interaction for users with visual impairments can provide design-
ers with the knowledge to better anticipate user needs in the development
of information technologies.
AMD aects central, high-resolution vision, which has a large impact on
an individual's ability to perform focus-intensive tasks, such as using a com-
puter 6 . Researchers have found that users with AMD tend to perform worse
than normally-sighted users, as measured by performance metrics such as
task times and errors, on simple computer-based tasks 2;3;4 . However, lit-
tle work has been done to examine how these performance decrements are
aected by increases in mental workload due to sensory impairments.
Measures of workload can be performance-based, survey-based, or physi-
ologically assessed. Pupil diameter is a well-documented, physiological mea-
sure of mental workload 7;8 . While research has shown pupillary response
behavior (PRB) to be related to changes in mental workload and task dif-
culty in a number of domains 9;10;11;12 , the complex control mechanism
of the pupil has made it dicult to extract the small, meaningful signals,
related to changes in mental workload from the larger, overall noisy signal
of PRB 13 .
Additionally, research in ophthalmology has shown that ocular disease
aecting the central visual eld { such as AMD { also has an eect on the
physiological mechanism controlling PRB 14;15 . This makes the PRB of in-